A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks
Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydra...
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-10-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/21/20/6909 |
_version_ | 1797513170327175168 |
---|---|
author | Juan Francisco Fuentes-Pérez Ana García-Vega Francisco Javier Bravo-Córdoba Francisco Javier Sanz-Ronda |
author_facet | Juan Francisco Fuentes-Pérez Ana García-Vega Francisco Javier Bravo-Córdoba Francisco Javier Sanz-Ronda |
author_sort | Juan Francisco Fuentes-Pérez |
collection | DOAJ |
description | Stepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (<i>Keras + TensorFlow</i>), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability. |
first_indexed | 2024-03-10T06:12:54Z |
format | Article |
id | doaj.art-f7a0a3845aac4acabd132d643baf1783 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-10T06:12:54Z |
publishDate | 2021-10-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-f7a0a3845aac4acabd132d643baf17832023-11-22T19:59:24ZengMDPI AGSensors1424-82202021-10-012120690910.3390/s21206909A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor NetworksJuan Francisco Fuentes-Pérez0Ana García-Vega1Francisco Javier Bravo-Córdoba2Francisco Javier Sanz-Ronda3Department of Hydraulics and Hydrology, ETSIIAA, University of Valladolid, 34004 Palencia, SpainCentro Tecnológico Agrario y Agroalimentario Itagra.ct, 34004 Palencia, SpainCentro Tecnológico Agrario y Agroalimentario Itagra.ct, 34004 Palencia, SpainDepartment of Hydraulics and Hydrology, ETSIIAA, University of Valladolid, 34004 Palencia, SpainStepped fishways are structures that allow the free movement of fish in transversal obstacles in rivers. However, the lack of or incorrect maintenance may deviate them from this objective. To handle this problem, this research work presents a novel low-cost sensor network that combines fishway hydraulics with neural networks programmed in Python (<i>Keras + TensorFlow</i>), generating the first autonomous obstruction/malfunction detection system for stepped fishways. The system is based on a network of custom-made ultrasonic water level nodes that transmit data and alarms remotely and in real-time. Its performance was assessed in a field study case as well as offline, considering the influence of the number of sensing nodes and obstruction dimensions. Results show that the proposed system can detect malfunctions and that allows monitoring of the hydraulic performance of the fishway. Consequently, it optimizes the timing of maintenance on fishways and, thus, has the potential of automatizing and reducing the cost of these operations as well as augmenting the service of these structures. Therefore, this novel tool is a step forward to achieve smart fishway management and to increase their operability.https://www.mdpi.com/1424-8220/21/20/6909water-level sensorslow-costhydraulic modelingfishwaysneural networksclogging |
spellingShingle | Juan Francisco Fuentes-Pérez Ana García-Vega Francisco Javier Bravo-Córdoba Francisco Javier Sanz-Ronda A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks Sensors water-level sensors low-cost hydraulic modeling fishways neural networks clogging |
title | A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks |
title_full | A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks |
title_fullStr | A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks |
title_full_unstemmed | A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks |
title_short | A Step to Smart Fishways: An Autonomous Obstruction Detection System Using Hydraulic Modeling and Sensor Networks |
title_sort | step to smart fishways an autonomous obstruction detection system using hydraulic modeling and sensor networks |
topic | water-level sensors low-cost hydraulic modeling fishways neural networks clogging |
url | https://www.mdpi.com/1424-8220/21/20/6909 |
work_keys_str_mv | AT juanfranciscofuentesperez asteptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT anagarciavega asteptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT franciscojavierbravocordoba asteptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT franciscojaviersanzronda asteptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT juanfranciscofuentesperez steptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT anagarciavega steptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT franciscojavierbravocordoba steptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks AT franciscojaviersanzronda steptosmartfishwaysanautonomousobstructiondetectionsystemusinghydraulicmodelingandsensornetworks |